Tailoring demand-reduction strategies for communities in India – the CEDRI project

This paper summarises the CEDRI method for quantifying baseline and future energy demand of a community – using a case-study community in Tamil- Nadu. The overall method includes modules relating to: i) dynamic building simulation for projecting future scenarios, ii) Hidden Markov Models for characterising and synthesising high resolution demand profiles, iii) Distributed Network modelling for performance issues in the local energy system, iv) results of co-production and householder engagement to help understand existing energy use, and identify likely future trends. Although the method is designed to be technology- agnostic, future scenarios are proposed to demonstrate the working of the model, and the kind of outputs and metrics that are achievable – and, crucially, why these might be useful to different actors and sectors involved with reducing energy demand in buildings. The work demonstrates that, for such diverse communities as can be found in India, replicability of method is more important than replicability of results. Rather than extrapolating the results of single case-study communities for much larger regions, CEDRI establishes a robust method that is agile enough to cope with different data limitations, building stocks, and behavioural approaches to comfort. The project also demonstrates the ability of dynamic building simulation to be used in conjunction with empirical energy data, network models, and qualitative information relating to cooling behaviour in specific populations. Although the method is designed to be technology-agnostic, future scenarios are proposed to demonstrate the working of the model, and the kind of outputs and metrics that are achievable – and, crucially, why these might be useful to different actors and sectors involved with reducing energy demand in buildings. The work demonstrates that, for such diverse communities as can be found in India, replicability of method is more important than replicability of results. Rather than extrapolating the results of single case-studies communities for much larger regions, CEDRI establishes a robust method that is agile enough to cope with different data limitations, building stocks, and behavioural approaches to comfort. The project also demonstrates the ability of dynamic building simulation to be used in conjunction with empirical energy data, network models, and qualitative information relating to cooling behaviour in specific populations.